Tableau Strategies: Solving Real, Practical Problems with Data Analytics
If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data.

Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work.

  • Use this book as a high-value on-the-job reference guide to Tableau
  • Visualize different data types and tackle specific data challenges
  • Create compelling data visualizations, dashboards, and data products
  • Learn how to generate industry-specific analytics
  • Explore categorical and quantitative analysis and comparisons
  • Understand geospatial, dynamic, statistical, and multivariate analysis
  • Communicate the value of the Tableau platform to your team and to stakeholders
1138695009
Tableau Strategies: Solving Real, Practical Problems with Data Analytics
If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data.

Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work.

  • Use this book as a high-value on-the-job reference guide to Tableau
  • Visualize different data types and tackle specific data challenges
  • Create compelling data visualizations, dashboards, and data products
  • Learn how to generate industry-specific analytics
  • Explore categorical and quantitative analysis and comparisons
  • Understand geospatial, dynamic, statistical, and multivariate analysis
  • Communicate the value of the Tableau platform to your team and to stakeholders
65.99 In Stock
Tableau Strategies: Solving Real, Practical Problems with Data Analytics

Tableau Strategies: Solving Real, Practical Problems with Data Analytics

Tableau Strategies: Solving Real, Practical Problems with Data Analytics

Tableau Strategies: Solving Real, Practical Problems with Data Analytics

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Overview

If you want to increase Tableau's value to your organization, this practical book has your back. Authors Ann Jackson and Luke Stanke guide data analysts through strategies for solving real-world analytics problems using Tableau. Starting with the basics and building toward advanced topics such as multidimensional analysis and user experience, you'll explore pragmatic and creative examples that you can apply to your own data.

Staying competitive today requires the ability to quickly analyze and visualize data and make data-driven decisions. With this guide, data practitioners and leaders alike will learn strategies for building compelling and purposeful visualizations, dashboards, and data products. Every chapter contains the why behind the solution and the technical knowledge you need to make it work.

  • Use this book as a high-value on-the-job reference guide to Tableau
  • Visualize different data types and tackle specific data challenges
  • Create compelling data visualizations, dashboards, and data products
  • Learn how to generate industry-specific analytics
  • Explore categorical and quantitative analysis and comparisons
  • Understand geospatial, dynamic, statistical, and multivariate analysis
  • Communicate the value of the Tableau platform to your team and to stakeholders

Product Details

ISBN-13: 9781492080084
Publisher: O'Reilly Media, Incorporated
Publication date: 09/28/2021
Pages: 575
Product dimensions: 7.00(w) x 9.19(h) x (d)

About the Author

Ann Jackson is founder and managing director at Jackson Two, a boutique consulting firm specializing in data analytics and visualization. In her practice, she empowers businesses to fully utilize their data assets. Ann has been recognized as a Tableau Zen Master for her proficiency with the product, her participation and leadership within the global community, and her contagious passion for data analytics.

Luke Stanke coleads an analytics consultancy firm that focuses on data visualization and advanced analytics. He’s worked for some of the largest companies. Luke has been recognized as a Tableau Zen Master multiple times for his proficiency with the product, his willingness to share knowledge, and his wish to inspire the Tableau community and solutions of tomorrow.

Table of Contents

Preface xi

1 Categorical Analysis 1

Bar Charts: Banco de Tableau Case Study 3

Strategy: Build a Bar Chart in Tableau 4

Strategy: Create a Top N Bar Chart 5

Strategy: Dynamically Group Other Dimensions 7

Strategy: Enhance Your Bar Chart with Color 8

Strategy: Left-align Text 9

Strategy: Create Bars with Labels on Top 10

Strategy: Create a Percent-of-Maximum Bar Chart 12

Bar-on-Bar Charts: Amplify Performance Case Study 13

Strategy: Create a Bar-on-Bar Chart 15

Treemaps: Amplify Performance Case Study 20

Strategy: Create a Basic Treemap 21

Strategy: Create Drillable Treemaps 22

Strategy: Encode a Continuous Measure with Color 23

Pie and Donut Charts: IT Employee Wellness Project Case Study 25

Strategy: Build a Basic Pie Chart 25

Strategy: Build a Donut Chart 26

Strategy: Create Small Multiples 28

Conclusion 28

2 Quantitative Analysis 31

Histograms: Office Essentials Case Study 32

Strategy: Make a Simple Histogram of Purchasing Behavior 33

Strategy: Create a Histogram with a Continuous Bin 37

Strategy: Use LOD Expressions in Histograms 38

Dot Plots and Jitterplots: Office Essentials Case Study 41

Strategy: Create a Basic Dot Plot 41

Strategy: Create a Jitterplot 42

Ranged Dot Plots: Office Essentials Case Study 44

Strategy: Create a Ranged Dot Plot 45

Strategy: Use Median and Leveraged Percentiles 47

Box Plots: Spear-Tukey Shipping Case Study 48

Strategy: Create a Basic Box Plot 50

Strategy: Combine a Box Plot and Histogram 54

Line Charts: Office Essentials Case Study 55

Strategy: Build a Line Chart 56

Strategy: Add Reference Distributions to a Line Chart 57

Strategy: Add a Standard Deviation to a Line Chart 59

Strategy: Use Reference Distributions as an Alerting Tactic 61

Calculated Dimensions Based on Statistics: Banco de Tableau Case Study 62

Strategy: Assign a Summary Statistical Value to Data Points 63

Pareto Charts: Amplify Performance (AP) Case Study 64

Strategy: Use Pareto Charts to Show Categorical Data 65

Conclusion 68

3 Making Comparisons 71

Bar Charts and Alternatives: Amplify Performance Case Study 72

Strategy: Compare with a Basic Bar Chart 73

Strategy: Convert a Vertical Bar Chart to Horizontal 74

Strategy: Create a Lollipop Chart 76

Strategy: Create a Basic Cleveland Dot Plot 81

Bar Charts for Rank Changes: AP Case Study 86

Strategy: Show Rank and Change of Rank on a Bar Chart 86

Bump Charts for Rank Changes over Multiple Periods: AP Case Study 96

Strategy: Make a Bump Chart 98

Barbell Plots for Hierarchical Data: Office Essentials Case Study 105

Strategy: Build a Barbell Plot 109

Trellis Charts/Small Multiples: Office Essentials Case Study 113

Strategy: Create a Trellis Chart for a Single Dimension 116

Parallel Coordinates Plots for Multiple Measures: OE Case Study 126

Strategy: Build a Parallel Coordinates Chart 128

Conclusion 137

4 Working with Time 139

Understanding Dates and Time 141

Date Parts and Date Values 142

Date Calculations 142

Date Hierarchies and Custom Dates 143

Discrete Versus Continuous Dates 144

Call Frequency: Chips and Bolts Call Center Case Study 146

Strategy: Determine Total Call Time by Hour 147

Strategy: Create a Plot to Measure Total Call Time by Minute 148

Strategy: Create a Continuous Datetime Axis by the Second 150

Strategy: Create a Continuous Datetime Axis for 15-Second Intervals 151

Strategy: Create a Continuous Datetime Axis for 15-Minute Intervals 152

Heatmaps (Highlight Tables) 154

Strategy: Build an Essential Heatmap 154

Strategy: Create a More Detailed Heatmap 155

Comparing Values Year-to-Date: CaB Call Center Case Study 157

Strategy: Show Progress to the Total by Using Two Bar Charts 159

Strategy: Compare Similar Periods on a Line Chart 161

Automated Reports 163

Automating Reports for Month-over-Month and Year-over-Year Change: CaB Call Center Case Study 163

Strategy: Automated Rolling Table 164

Nonstandard Calendars 167

Strategy: Build a Monthly Bar Chart with a June 1 Fiscal Year Start 169

Visualizing the 4-5-4 Calendar: Office Essentials Case Study 170

Strategy: Build a Bar Chart Using the 4-5-4 Retail Calendar 171

Conclusion 175

5 Key Performance Indicators 177

Displaying KPIs 179

Displaying KPIs: Office Essentials Case Study 180

Strategy: Designing Clear KPIs 181

Strategy: Create Single-Sheet KPIs 183

Strategy: Automate Your KPIs 184

Strategy: Create Year-over-Year Calculations 187

Sparklines 190

Sparklines: Office Essentials Case Study 190

Strategy: Create Sparklines 190

Strategy: Create Year-to-Date Sparklines 193

Strategy: Create Rolling 24-Month Sparklines 194

Strategy: Build Delta Spark Bars 195

Strategy: Progress to Target 196

Multiple KPIs as a Scorecard 199

KPI Scorecard: Office Essentials Case Study 199

Strategy: Create Aggregate KPIs 201

Tracking Daily Changes: Office Essentials Case Study 203

Strategy: Create Month-to-Date Sparklines 204

Strategy: Create Month-to-Date KPIs 209

Strategy: Combine KPI Visualizations in a Dashboard 211

Conclusion 212

6 Building Impactful Tables 215

Building Great Tables 216

Ensure a Clear Purpose for Your Table 218

Format Your Table to Maximize Readability 218

Using Color in Tables: Office Essentials Case Study 219

Strategy: Create a Table Using Limited Color 219

Strategy: Encode Color with Dots 226

Moving Beyond Measure Names and Values: Office Essentials Case Study 230

Strategy: Create a Table Body Without Measure Names or Measure Values 232

Strategy: Create Table Headers Without Measure Names or Measure Values 238

Strategy: Use Measures as Headers 240

Problem-Solving with Subsets and Hiding the Dreaded Abc: Office Essentials Case Study 250

Strategy: Show the Top Products Within Sub-Categories 251

Strategy: Hide the Abc 257

Conclusion 258

7 Working with Geospatial Data 261

Choropleth (Filled) Maps 262

Displaying Customer Penetration with Choropleth Maps: Office Essentials Case Study 263

Strategy: Create a Simple Choropleth Map 263

Strategy: Normalize a Choropleth Map 264

Strategy: Add a Custom Color Palette 266

Strategy: Make a Decile Choropleth Map 268

Symbol Maps 270

Using Symbol Maps to Show Profitability and Channel Distribution: OE Case Study 270

Strategy: Create a Symbol Map 271

Strategy: Create a Map with Donut Charts 273

Tile Maps (Cartograms) 274

Showing Education Level with a Tile Map: Aloft Educational Services Case Study 274

Strategy: Build a Square Tile Map 275

Strategy: Compare Parts Against the Whole with a Tile Map 277

Built-in Features and Functions 279

Using Built-in Features and Functions with Marketing Data: Sage Digital Marketing Case Study 279

Strategy: Build Custom Polygons Using Groups 279

Strategy: Build Custom Polygons Using Underlying Geographic Data 283

Strategy: Use the Distance Function to Show Zip Codes' Distance from a Central Location 284

Strategy: Use the Buffer Function to Map a Trade Area Using Radial Distance 286

Strategy: Create Paths Between a Starting Point and Destinations with MakePoint and MakeLine 288

Conclusion 289

8 Advanced Mathematical Concepts 291

Forecasting 292

Using Forecasting to Predict Staffing Needs: CaB Call Center Case Study 293

Strategy: Create a Monthly Forecast 293

Relationships Between Two Numerical Values 297

Using Scatter Plots to See Relationships Between Spend and Conversions: Sage Digital Marketing Case Study 299

Strategy: Create a Scatter Plot 299

Strategy: Create a Quadrant Chart 300

Strategy: Add a Trend Line to a Scatter Plot 305

Cluster Analysis 308

Creating Segmentation Among Employees to Assess Differences in Attrition: Banco de Tableau Case Study 309

Strategy: Add Cluster Analysis to a Scatter Plot and Use Analysis in Another Chart 309

Alternative Axis and Many Multiples 313

Tracking Positive Cases of Covid-19 Globally: Logistics Case Study 314

Strategy: Use a Logarithmic Axis to Understand Rate of Change 314

Strategy: Normalize a Date Axis 316

Strategy: Create a Trellis Chart 318

Advanced Modeling Using Statistical Add-Ons 321

Using Python Analytics Extension for Web Page A/B Testing: Squeaks Pet Supply Case Study 323

Sentiment Analysis on Customer Reviews: Amazing Products Case Study 327

Conclusion 329

9 Constructing Dynamic Analyses 331

Parameters 332

Using Parameters to Change Measures and Dimensions: Office Essentials Case Study 332

Strategy: Use a Parameter to Change a Measure in a Bar Chart 333

Strategy: Use Regex Functions to Dynamically Format a Parameterized Metric 335

Strategy: Use a Parameter to Change the Dimension in a Bar Chart 336

Using Parameters to Set Time Periods and Date Aggregations in Line Charts: Office Essentials Case Study 337

Strategy: Use a Parameter to Change the Date in a Line Chart 338

Strategy: Add Hidden Date Filters to Prevent Truncated Time Parts 339

Using Parameter Actions to Change Trended Metrics: Sage Digital Marketing Case Study 341

Strategy: Change a Metric Dynamically Using Parameter Actions and Measure Names 341

Using Parameter Actions to View Daily and 7-Day Average Value: Sage Digital Marketing Case Study 344

Strategy: Compute a 7-Day Moving Average Reference Line That Dynamically Changes with a Date Selection 345

Sets and Set Actions 346

Using Set Actions to Drill Down and Filter Data: Digital Marketing Case Study 347

Strategy: Drill from Week to Date in a Line Chart 348

Strategy: Expand a Section of a Data Table 350

Animation 352

Competitor Analysis Study: Using Animations to Compare Ranking Performance 352

Strategy: Build an Animated Bump Chart 353

Strategy: Create a Racing Bar Chart 355

Conclusion 357

10 Advanced Data Modeling 359

Data Modeling 360

Strategy: Create a Calendar with Data Densification 362

Strategy: Create Rounded Bar Charts 367

Strategy: Create an Accordion Table 375

Strategy; Create a Sales Funnel 382

Market Basket Analysis 391

Strategy: Basket Analysis 393

Strategy: Build a Multidimension Waterfall 401

Strategy: Layer Marks with Maps Without Making a Map 413

Conclusion 424

Further Reading 424

11 Advanced Interactivity 425

Sheet Swapping with Parameters and Parameter Actions: Superstore Case Study 426

Strategy: Use Parameter-Based Sheet Swapping 428

Strategy: Use a Parameter-Action Sheet Swap 432

Strategy: Automatically Deselect Marks 437

Using Parameters and Parameter Actions to Create Multiple Select Parameters: Superstore Case Study 439

Strategy: Create a Multiple-Select Parameter 440

Swapping Metrics Using Parameter Actions: Office Essentials Case Study 447

Strategy: Use Sheets as Buttons 448

Adding Pagination to Tables with Parameters, Parameter Actions: Superstore Case Study 455

Strategy: Add Table Pagination 457

Creating Dynamic, Single-Click Drill-Throughs: Superstore Case Study 472

Strategy: Build Drill-Through Interactivity 473

Conclusion 478

Further Reading 479

12 Building Dashboards and Data Products 481

Dashboard Design 482

Know Your Audience 482

Dashboard Types 484

Mobile Dashboard Design 489

Design Details 490

Strategy: Display Different Visuals for Desktop and Mobile 495

Accessibility 500

Dyslexia 500

Color and Visual Impairment 514

Formatting Consistency 519

Rounding Numbers 519

Axes Versus Labels 520

Font Styling 523

Conclusion 524

13 The Broader Tableau Ecosystem 527

Data Preparation: Where and When 527

Spreadsheets: Microsoft Excel 528

Traditional Data Preparation: SQL 529

Modern Data Preparation: ELT Tools 531

Review 532

Building a Thriving Analytics Platform 532

Future Trends 535

Data Journalism and the Rise of Data Storytelling 536

Analytics Within Human Workflows 536

Analytics as a Product 537

Conclusion 538

14 Industry Frameworks 539

Healthcare 540

Education 541

Elementary, Middle, and High School 542

College and University 542

Logistics 543

Marketing 543

Sales 544

Retail 545

Finance 545

Conclusion 546

Index 547

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